Data science has been the biggest buzzword in business analytics since 2012, when Harvard Business Review declared it the “sexiest” job. In the years that followed, applications of data science proliferated. Innovative disruptors like Uber use data science to predict the needs of their customers, and even smaller outfits, like Farmstead Table, a restaurant outside of Boston, can leverage data science through ready-made solutions. Data science is revolutionizing businesses small and large alike.
But what is it? Data Science is the practice of turning raw data into actionable insights. Consider the Netflix series House of Cards: Netflix tracked and analyzed the behavior of 33 million subscribers to reveal a hole in the marketplace for a show like House of Cards, its first original series and, thanks to the power of data science, now a household name.
According to Forbes and the International Institute for Analytics, the productivity benefits of data science will reach $430 billion by 2020. The amount of data being generated continues to expand and methods of processing data into useful information continue to improve. Forbes also wagers that a relatively new executive position, the chief data officer, will come into prominence. It is a prediction which draws attention to the largest hurdle that currently exists for businesses looking to integrate data science with their operations: a shortage of qualified talent.
While the U.S. Bureau of Labor Statistics does not maintain figures on data scientists in particular, it does track the employment of and predict the need for statisticians, of which it considers data scientists to be a subsection. Based on BLS figures, the employment of statisticians is projected to increase by 34 percent between 2014 to 2024, five times more than the average for all occupations. This explosive demand will squeeze the already threadbare supply. A study by the consulting firm McKinsey & Company estimates that the shortage of qualified data scientists will be between 140,000 to 190,000 by 2018 in the United States alone.
So what are today’s chief information officers and chief technology officers to do in preparation for the data scientist crunch to come? The dearth of available talent can be met in two ways:
- Invest in your employees
The market for data scientists is set to become a pretty ruthless place; you and your business can avoid this by nurturing the talent on your team. Data science involves a series of interdisciplinary practices drawing upon techniques and theories from statistics, information science and computer science. While not every company employs an in-house statistician, chances are good that you do have someone familiar with information or computer science on the payroll. Rather than hunting for a prized data scientist on the open market, encourage your most able employee to become a data scientist through continuing education.
Master’s degrees in data science are not uncommon nowadays. A particularly attractive avenue may be through the University of California Berkeley School of Information, which unveiled the first fully online Master of Information and Data Science program in the world. The program, which enables students to obtain their degrees without visiting campus, is ideal for employers insofar as it allows employees to meet their academic obligations without sacrificing their professional ones.
- Make strategic partnerships
A second method of obtaining the data science skills your business needs is through alliance rather than cultivation. No company is an island. Every business relies on a network of partners, suppliers and distributors that contribute to its success. Professional services firms can offer big data services or data science services. The advantage here is that these organizations already have the expertise of handling and analyzing large data sets, such as from a Hadoop cluster. Services firms can also help you deploy and customize specialist software analytics platforms, such as those by SAS. Finally there is also the option of working with a technology partner to develop your own big data platform, for example based on Hadoop or NoSQL databases, or other open source technologies.
The dawn of data science has come and businesses are only beginning to bask in its light. And remember, you don’t need to be a large enterprise to benefit from data science. For example, consider the case of Twiddy & Company, a North Carolina realtor: Using analytics tools, Twiddy & Company optimized the rentals of the 998 homes they manage, determining when and how much to raise prices to take advantage of high-demand seasons, as well as lowering them to shore up low-demand ones. Companies who position themselves to take full advantage of these developments are reaping the rewards, putting them well ahead of the competition. Those benefits will be magnified as data science continues to progress. Though it may seem difficult or even unnecessary to make room for a data scientist in your business right now, before long it will be impossible not to.